# A tibble: 6 × 4
anxiety flexibility mindfulness activity
<dbl> <dbl> <chr> <chr>
1 50.2 44.4 no pilates
2 31.5 47.7 yes altro
3 34.0 65.6 no pilates
4 37.1 50.7 no altro
5 48.3 51.3 no altro
6 16.9 67.2 yes altro
Other
see this specific code
head(data)# A tibble: 6 × 4
anxiety flexibility mindfulness activity
<dbl> <dbl> <chr> <chr>
1 50.2 44.4 no pilates
2 31.5 47.7 yes altro
3 34.0 65.6 no pilates
4 37.1 50.7 no altro
5 48.3 51.3 no altro
6 16.9 67.2 yes altro
see this specific code
```{r}
#| code-fold: true
#| code-summary: see this specific code
head(data)
```# A tibble: 6 × 4
anxiety flexibility mindfulness activity
<dbl> <dbl> <chr> <chr>
1 50.2 44.4 no pilates
2 31.5 47.7 yes altro
3 34.0 65.6 no pilates
4 37.1 50.7 no altro
5 48.3 51.3 no altro
6 16.9 67.2 yes altro
see this specific code
```{r}
#| code-fold: true
#| code-summary: see this specific code
str(data)
```spc_tbl_ [300 × 4] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
$ anxiety : num [1:300] 50.2 31.5 34 37.1 48.3 ...
$ flexibility: num [1:300] 44.4 47.7 65.6 50.7 51.3 ...
$ mindfulness: chr [1:300] "no" "yes" "no" "no" ...
$ activity : chr [1:300] "pilates" "altro" "pilates" "altro" ...
- attr(*, "spec")=
.. cols(
.. anxiety = col_double(),
.. flexibility = col_double(),
.. mindfulness = col_character(),
.. activity = col_character()
.. )
- attr(*, "problems")=<externalptr>
see this specific code
summary(data) anxiety flexibility mindfulness activity
Min. : 1.483 Min. :26.91 Length:300 Length:300
1st Qu.:25.977 1st Qu.:44.24 Class :character Class :character
Median :33.922 Median :49.56 Mode :character Mode :character
Mean :33.418 Mean :50.34
3rd Qu.:41.974 3rd Qu.:56.32
Max. :64.775 Max. :82.41
see this specific code
```{r}
#| code-fold: true
#| code-summary: see this specific code
summary(data)
``` anxiety flexibility mindfulness activity
Min. : 1.483 Min. :26.91 Length:300 Length:300
1st Qu.:25.977 1st Qu.:44.24 Class :character Class :character
Median :33.922 Median :49.56 Mode :character Mode :character
Mean :33.418 Mean :50.34
3rd Qu.:41.974 3rd Qu.:56.32
Max. :64.775 Max. :82.41
Table of the data for anxiety and flexibility
Table 1 illustrates the characteristics of the population of interest
knitr::kable(head(data))| anxiety | flexibility | mindfulness | activity |
|---|---|---|---|
| 50.17244 | 44.39524 | no | pilates |
| 31.47451 | 47.69823 | yes | altro |
| 34.03981 | 65.58708 | no | pilates |
| 37.06712 | 50.70508 | no | altro |
| 48.30549 | 51.29288 | no | altro |
| 16.94087 | 67.15065 | yes | altro |
?@lst-table1 illustrates a basic use of the kable() function
Correlation between anxiety and flexibility stratified based on mindfulness
?@lst-plot1 illustrates a basic use of the function plot()
see this specific code
ggplot(data,
aes(x=flexibility, y=anxiety, color=mindfulness)) +
geom_point()Figure and table
ggplot(mtcars,
aes(hp, mpg, color = factor(am))) +
geom_point() +
geom_smooth(formula = y ~ x, method = "loess") +
theme(legend.position = 'bottom')datatable(mtcars,
options = list(pageLength = 5))knitr::kable(head(mtcars))| mpg | cyl | disp | hp | drat | wt | qsec | vs | am | gear | carb | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Mazda RX4 | 21.0 | 6 | 160 | 110 | 3.90 | 2.620 | 16.46 | 0 | 1 | 4 | 4 |
| Mazda RX4 Wag | 21.0 | 6 | 160 | 110 | 3.90 | 2.875 | 17.02 | 0 | 1 | 4 | 4 |
| Datsun 710 | 22.8 | 4 | 108 | 93 | 3.85 | 2.320 | 18.61 | 1 | 1 | 4 | 1 |
| Hornet 4 Drive | 21.4 | 6 | 258 | 110 | 3.08 | 3.215 | 19.44 | 1 | 0 | 3 | 1 |
| Hornet Sportabout | 18.7 | 8 | 360 | 175 | 3.15 | 3.440 | 17.02 | 0 | 0 | 3 | 2 |
| Valiant | 18.1 | 6 | 225 | 105 | 2.76 | 3.460 | 20.22 | 1 | 0 | 3 | 1 |
ggplot(mtcars,
aes(hp, mpg, color = factor(am))) +
geom_point() +
geom_smooth(formula = y ~ x, method = "loess") +
theme(legend.position = 'bottom')Multiple plots Figure 2 illustrates different things. Figure 2 (a) illustrates the correlation between anxiety and flexibility, Figure 2 (b) illustrates the polynomial regression model, Figure 2 (c) the Linear regression model, Figure 2 (d) the GLM with Poisson
Table 2 presents two datasets: Table 2 (a) is cars and Table 2 (b) is pressure
Table 2: Datasets
| speed | dist |
|---|---|
| 4 | 2 |
| 4 | 10 |
| 7 | 4 |
| 7 | 22 |
| 8 | 16 |
| 9 | 10 |
| temperature | pressure |
|---|---|
| 0 | 0.0002 |
| 20 | 0.0012 |
| 40 | 0.0060 |
| 60 | 0.0300 |
| 80 | 0.0900 |
| 100 | 0.2700 |
#Annotation
mtcars %>%
ggplot( aes(mpg, hp, size = gear)) +
geom_point() +
geom_smooth(method = "lm")- 1
- This does that
- 2
- This other thing is this
- 3
- And look at this!
- 4
- Please have mercy
`geom_smooth()` using formula = 'y ~ x'
The mean of the gear variable in mtcars is mean(mtcars$gear)
The mean of the gear variable in mtcars is 3.6875